Operations | Monitoring | ITSM | DevOps | Cloud

OpenLLMetry extends the industry-standard OpenTelemetry framework with features specifically for monitoring large language model (LLM) and GenAI application behavior.

There’s a new kind of thinking happening in the world. It doesn’t come with memories, emotions, or doubt. It doesn’t hesitate. It doesn’t wonder. However, it appears to be thinking. Ask it a question, and it responds in perfect grammar. Ask for help, and it gives you options. You could almost believe it understands. Almost. This is what happens when machines are trained to speak like us, but without ever needing to understand us.

Ever look at your to-do list at the end of the day and realize it’s grown longer, not shorter? We get it—there’s always more to do and never enough time. But if you’re a Sumo Logic user, reading this blog will be a win for your day because we’re giving you six ways to slash the time you spend on tasks in your platform.

Platform teams are struggling with observability noise, bloated storage costs, and lack of clarity during incidents. Most teams capture everything all the time, leading to expensive, overwhelming, and often unnecessary data volumes. In Telemetry for Modern Apps, Mezmo teamed up with Checkly to demonstrate how synthetic monitoring triggers and responsive telemetry pipelines can help reduce costs while maintaining the context needed during incidents.

You're running Kafka on Confluent Cloud. You care about lag, throughput, retries, and replication. But where do you see those metrics? Confluent gives you metrics, sure, but not all in one place. Some live behind a metrics API, others behind Connect clusters or Schema Registries. You either wire them manually or give up. What if you could stream those metrics to a platform built for high-frequency, high-cardinality time series, and do it in minutes?

Remember when JavaScript was just for making snowflakes fall on your GeoCities page? Those were simpler times. Now we’re building entire applications in the browser, and surprise! JavaScript wasn’t exactly designed with memory management in mind. While other languages have garbage collectors that actually, you know, collect garbage, JavaScript’s garbage collector is more like that roommate who promises to clean but just shoves everything under the bed. The real kicker?